Search results for: surface water quality

Authors: Karishma Kashyap, Subha D. Parida

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Rapid population growth and urbanization is creating pressure throughout the world. This has a dramatic effect on a lot of elements which include water, food, transportation, energy, infrastructure etc. as few of the key services. Built environment sector is growing concurrently to meet the needs of urbanization. Due to such large scale development of buildings, there is a need for them to be monitored and managed efficiently. Along with appropriate management, climate adaptation is highly crucial as well because buildings are one of the major sources of greenhouse gas emission in their operation phase. Buildings to be adaptive need to provide a triple bottom approach to sustainability i.e., being socially, environmentally and economically sustainable. Hence, in order to deliver these sustainability outcomes, there is a growing understanding and thrive towards switching to green buildings or renovating new ones as per green standards wherever possible. Academic institutions in particular have been following this trend globally. This is highly significant as universities usually have high occupancy rates because they manage a large building portfolio. Also, as universities accommodate the future generation of architects, policy makers etc., they have the potential of setting themselves as a best industry practice model for research and innovation for the rest to follow. Hence their climate adaptation, sustainable growth and performance management becomes highly crucial in order to provide the best services to users. With the objective of evaluating appropriate management mechanisms within academic institutions, a feasibility study was carried out in a recent 5-Star Green Star rated university building (housing the School of Construction) in Victoria (south-eastern state of Australia). The key aim was to understand the behavioral and social aspect of the building users, management and the impact of their relationship on overall building sustainability. A survey was used to understand the building occupant’s response and reactions in terms of their work environment and management. A report was generated based on the survey results complemented with utility and performance data which were then used to evaluate the management structure of the university. Followed by the report, interviews were scheduled with the facility and asset managers in order to understand the approach they use to manage the different buildings in their university campuses (old, new, refurbished), respective building and parameters incorporated in maintaining the Green Star performance. The results aimed at closing the communication and feedback loop within the respective institutions and assist the facility managers to deliver appropriate stakeholder engagement. For the wider design community, analysis of the data highlights the applicability and significance of prioritizing key stakeholders, integrating desired engagement policies within an institution’s management structures and frameworks and their effect on building performance

Keywords: building optimization, green building, post occupancy evaluation, stakeholder engagement

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Authors: Wisam H. Benamer, Ehab A. Elfallah, Mohamed A. Elshaari, Farag A. Elshaari

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A challenge for laboratories is to provide bacterial identification and antibiotic sensitivity results within a short time. Hence, advancement in the required technology is desirable to improve timing, accuracy and quality. Even with the current advances in methods used for both phenotypic and genotypic identification of bacteria the need is there to develop method(s) that enhance the outcome of bacteriology laboratories in accuracy and time. The hypothesis introduced here is based on the assumption that the chromosome of any bacteria contains unique sequences that can be used for its identification and typing. The outcome of a pilot study designed to test this hypothesis is reported in this manuscript. Methods: The complete chromosome sequences of several bacterial species were downloaded to use as search targets for unique sequences. Visual basic and SQL server (2014) were used to generate a complete set of 18-base long primers, a process started with reverse translation of randomly chosen 6 amino acids to limit the number of the generated primers. In addition, the software used to scan the downloaded chromosomes using the generated primers for similarities was designed, and the resulting hits were classified according to the number of similar chromosomal sequences, i.e., unique or otherwise. Results: All primers that had identical/similar sequences in the selected genome sequence(s) were classified according to the number of hits in the chromosomes search. Those that were identical to a single site on a single bacterial chromosome were referred to as unique. On the other hand, most generated primers sequences were identical to multiple sites on a single or multiple chromosomes. Following scanning, the generated primers were classified based on ability to differentiate between medically important bacterial and the initial results looks promising. Conclusion: A simple strategy that started by generating primers was introduced; the primers were used to screen bacterial genomes for match. Primer(s) that were uniquely identical to specific DNA sequence on a specific bacterial chromosome were selected. The identified unique sequence can be used in different molecular diagnostic techniques, possibly to identify bacteria. In addition, a single primer that can identify multiple sites in a single chromosome can be exploited for region or genome identification. Although genomes sequences draft of isolates of organism DNA enable high throughput primer design using alignment strategy, and this enhances diagnostic performance in comparison to traditional molecular assays. In this method the generated primers can be used to identify an organism before the draft sequence is completed. In addition, the generated primers can be used to build a bank for easy access of the primers that can be used to identify bacteria.

Keywords: bacteria chromosome, bacterial identification, sequence, primer generation

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Authors: Danylo Brindak, Viktor Liashko, Olexander Chepurniy

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Despite considerable experience in implementation of the best international approaches and services within response to epidemy of multi-drug resistant tuberculosis, the results of situation analysis indicate the presence of faults in this area. In 2014, Ukraine (for the first time) was included in the world’s five countries with the highest level of drug-resistant tuberculosis. The effectiveness of its treatment constitutes only 35% in the country. In this context, the increase in allocation of funds to control the epidemic of multidrug-resistant tuberculosis does not produce perceptible positive results. During 2001-2016, only the Global Fund to fight AIDS, Tuberculosis, and Malaria allocated to Ukraine more than USD 521,3 million for programs of tuberculosis and HIV/AIDS control. However, current conditions in post-Semashko system create little motivation for rational use of resources or cost control at inpatient TB facilities. There is no motivation to reduce overdue hospitalization and to target resources to priority sectors of modern tuberculosis control, including a model of care focused on the patient. In the presence of a line-item budget at medical institutions, based on the input factors as the ratios of beds and staff, there is a passive disposal of budgetary funds by health care institutions and their employees who have no motivation to improve quality and efficiency of service provision. Outpatient treatment of tuberculosis is being implemented in Ukraine since 2011 and has many risks, namely creation of parallel systems, low consistency through dependence on funding for the project, reduced the role of the family doctor, the fragmentation of financing, etc. In terms of reforming approaches to health system financing, which began in Ukraine in late 2016, NGO Infection Control in Ukraine conducted piloting of a new, motivating method of remuneration of employees in primary health care. The innovative aspect of this funding mechanism is cost according to results of treatment. The existing method of payment on the basis of the standard per inhabitant (per capita ratio) was added with motivating costs according to results of work. The effectiveness of such treatment of TB patients at the outpatient stage is 90%, while in whole on the basis of a current system the effectiveness of treatment of newly diagnosed pulmonary TB with positive swab is around 60% in the country. Even though Ukraine has 5.24 TB beds per 10 000 citizens. Implemented pilot model of ambulatory treatment will be used for the creation of costs system according to results of activities, the integration of TB and primary health and social services and their focus on achieving results, the reduction of inpatient treatment of tuberculosis.

Keywords: health care reform, multi-drug resistant tuberculosis, outpatient treatment efficiency, tuberculosis

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Authors: Keng-hui Lin

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Evidence-based policing (EBP) has seen significant global expansion, marked by the development of professional societies, practitioner-focused training, and research translation tools. These advancements have redefined policing as a profession requiring analytical skills, research-informed decision-making, and a commitment to evidence-based practices. However, widespread acceptance of EBP among police officers remains challenging, with key barriers including disagreements over the definition and quality of research evidence, a scarcity of accessible evidence, and philosophical differences between practitioners and researchers. The most critical obstacle, however, is resistance to integrating research evidence into policing practices. The successful institutionalization of EBP within policing hinges on the receptivity of police officers. While existing literature focuses on Anglo-American contexts, there is a paucity of studies examining how officers in non-Western contexts, such as Taiwan, perceive and utilize science in policing. To address this gap, this study explores officer receptivity to EBP within three police departments in Taiwan: Taichung City Police Department (TCPD), Hsinchu County Police Department (HCPD), and Chiayi County Police Department (CCPD), which serve urban, suburban, and rural areas, respectively. With cooperation from departmental commissioners, 496, 477, and 219 officers from these respective departments participated in the study. Utilizing the survey designed by Telep and Lum, this research compares receptivity to EBP between officers in Taiwan, Canada (across seven departments), and the United States (across three departments). The findings reveal distinctive attitudes towards science in policing among Taiwanese officers compared to their Canadian and American counterparts. For instance, 63.3% of Canadian officers reported reading professional journals or magazines in the past six months, while this figure was approximately 30% for both American and Taiwanese officers. In terms of using materials produced by analysts in their daily work, over 70% of American officers (except those from the Sacramento Police Department) reported frequent usage, compared to around 45% of Taiwanese officers and 60.7% of Canadian officers. When considering the balance between scientific research and personal experience in decision-making, around 60% of Canadian and Taiwanese officers favoured experience, whereas over 70% of American officers held this view. Additionally, while around 80% of Canadian and American officers strongly agreed or agreed on the necessity of collaboration with researchers to enhance crime reduction efforts, only about 60% of Taiwanese officers shared this sentiment. This study represents, to our knowledge, the first examination of officer receptivity to EBP in Asia, offering critical insights into the challenges faced in advancing the professionalization of policing in Taiwan. The findings suggest that Taiwanese officers may hold more resistant attitudes toward EBP, highlighting the need for further exploration of the obstacles to fostering openness to research in policing.

Keywords: evidence-based policing, receptivity, comparative study, democratic policing, Taiwan

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Authors: Yohannes Haile, Dipo Onipede, Jr., Omar Ashour

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The main thrust of our research is to determine Industry 4.0 readiness of small and mid-size manufacturing companies in our region and assist them to implement Cyber Physical Production System (CPPS) capabilities. Adopting CPPS capabilities will help organizations realize improved quality, order delivery, throughput, new value creation, and reduced idle time of machines and work centers of their manufacturing operations. The key metrics for the assessment include the level of intelligence, internal and external connections, responsiveness to internal and external environmental changes, capabilities for customization of products with reference to cost, level of additive manufacturing, automation, and robotics integration, and capabilities to manufacture hybrid products in the near term, where near term is defined as 0 to 18 months. In our initial evaluation of several manufacturing firms which are profitable and successful in what they do, we found low level of Physical-Digital-Physical (PDP) loop in their manufacturing operations, whereas 100% of the firms included in this research have specialized manufacturing core competencies that have differentiated them from their competitors. The level of automation and robotics integration is low to medium range, where low is defined as less than 30%, and medium is defined as 30 to 70% of manufacturing operation to include automation and robotics. However, there is a significant drive to include these capabilities at the present time. As it pertains to intelligence and connection of manufacturing systems, it is observed to be low with significant variance in tying manufacturing operations management to Enterprise Resource Planning (ERP). Furthermore, it is observed that the integration of additive manufacturing in general, 3D printing, in particular, to be low, but with significant upside of integrating it in their manufacturing operations in the near future. To hasten the readiness of the local and regional manufacturing companies to Industry 4.0 and transitions towards CPPS capabilities, our working group (ADMAR Working Group) in partnership with our university have been engaged with the local and regional manufacturing companies. The goal is to increase awareness, share know-how and capabilities, initiate joint projects, and investigate the possibility of establishing the Center for Cyber Physical Production Systems Innovation (C2P2SI). The center is intended to support the local and regional university-industry research of implementing intelligent factories, enhance new value creation through disruptive innovations, the development of hybrid and data enhanced products, and the creation of digital manufacturing enterprises. All these efforts will enhance local and regional economic development and educate students that have well developed knowledge and applications of cyber physical manufacturing systems and Industry 4.0.

Keywords: automation, cyber-physical production system, digital manufacturing enterprises, disruptive innovation, new value creation, physical-digital-physical loop

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Authors: Jasmeet Kaur, Anup Singh, Shashikant Iyengar, Arun Kumar, Ira Sahay

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Latent autoimmune diabetes in adults (LADA) is an irreversible autoimmune disease that affects insulin production. LADA is characterized by the production of Glutamic acid decarboxylase (GAD) antibodies, which is similar to type 1 diabetes. Individuals with LADA may eventually develop overt diabetes and require insulin. In this condition, the pancreas produces little or no insulin, which is a hormone used by the body to allow glucose to enter cells and produce energy. While type 1 diabetes was traditionally associated with children and teenagers, its prevalence has increased in adults as well. LADA is frequently misdiagnosed as type 2 diabetes, especially in adulthood when type 2 diabetes is more common. LADA develops in adulthood, usually after age 30. Managing LADA involves metabolic control with exogenous insulin and prolonging the life of surviving beta cells, thereby slowing the disease's progression. This case study examines the impact of approximately 3 months of low-carbohydrate dietary intervention in a 42-year-old woman with LADA who was initially misdiagnosed as having type 2 diabetes. Her c-peptide was 0.13 and her HbA1c was 9.3% when this trial began. Low-carbohydrate interventions have been shown to improve blood sugar levels, including fasting, post-meal, and random blood sugar levels, as well as haemoglobin levels, blood pressure, energy levels, sleep quality, and satiety levels. The use of low-carbohydrate dietary intervention significantly reduces both hypo- and hyperglycaemia events. During the 3 months of the study, there were 2 to 3 hyperglycaemic events owing to physical stress and a single hypoglycaemic event. Low-carbohydrate dietary therapies lessen insulin dose inaccuracy, which explains why there were fewer hyperglycaemic and hypoglycaemic events. In three months, the glycated haemoglobin (HbA1c) level was reduced from 9.3% to 6.3%. These improvements occur without the need for caloric restriction or physical activity. Stress management was crucial aspect of the treatment plan as stress-induced neuroendocrine hormones can cause immunological dysregulation. Additionally, supplements that support immune system and reduce inflammation were used as part of the treatment during the trial. Long-term studies are needed to track disease development and corroborate the claim that such dietary treatments can prolong the honeymoon phase in LADA. Various factors can contribute to additional autoimmune attacks, so measuring c-peptide is crucial on a regular basis to determine whether insulin levels need to be adjusted.

Keywords: autoimmune, diabetes, LADA, low_carb, nutrition

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Authors: Fatemeh Sadeghi, Peyman Sheikhzadeh

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Introduction: Block Sequential Regularized Expectation Maximization (BSREM) reconstruction algorithm was recently developed to suppress excessive noise by applying a relative difference penalty. The aim of this study was to investigate the effect of various strengths of noise penalization factor in the BSREM algorithm under different acquisition duration and lesion sizes in order to determine an optimum penalty factor by considering both quantitative and qualitative image evaluation parameters in clinical uses. Materials and Methods: The NEMA IQ phantom and 15 clinical whole-body patients with prostate cancer were evaluated. Phantom and patients were injected withGallium-68 Prostate-Specific Membrane Antigen(68 Ga-PSMA)and scanned on a non-time-of-flight Discovery IQ Positron Emission Tomography/Computed Tomography(PET/CT) scanner with BGO crystals. The data were reconstructed using BSREM with a β-value of 100-500 at an interval of 100. These reconstructions were compared to OSEM as a widely used reconstruction algorithm. Following the standard NEMA measurement procedure, background variability (BV), recovery coefficient (RC), contrast recovery (CR) and residual lung error (LE) from phantom data and signal-to-noise ratio (SNR), signal-to-background ratio (SBR) and tumor SUV from clinical data were measured. Qualitative features of clinical images visually were ranked by one nuclear medicine expert. Results: The β-value acts as a noise suppression factor, so BSREM showed a decreasing image noise with an increasing β-value. BSREM, with a β-value of 400 at a decreased acquisition duration (2 min/ bp), made an approximately equal noise level with OSEM at an increased acquisition duration (5 min/ bp). For the β-value of 400 at 2 min/bp duration, SNR increased by 43.7%, and LE decreased by 62%, compared with OSEM at a 5 min/bp duration. In both phantom and clinical data, an increase in the β-value is translated into a decrease in SUV. The lowest level of SUV and noise were reached with the highest β-value (β=500), resulting in the highest SNR and lowest SBR due to the greater noise reduction than SUV reduction at the highest β-value. In compression of BSREM with different β-values, the relative difference in the quantitative parameters was generally larger for smaller lesions. As the β-value decreased from 500 to 100, the increase in CR was 160.2% for the smallest sphere (10mm) and 12.6% for the largest sphere (37mm), and the trend was similar for SNR (-58.4% and -20.5%, respectively). BSREM visually was ranked more than OSEM in all Qualitative features. Conclusions: The BSREM algorithm using more iteration numbers leads to more quantitative accuracy without excessive noise, which translates into higher overall image quality and lesion detectability. This improvement can be used to shorter acquisition time.

Keywords: BSREM reconstruction, PET/CT imaging, noise penalization, quantification accuracy

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Authors: Mohamed M. Zaki, Maha M. Hady

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Salmonella spp. have been categorized as the world’s biggest threats to human health and poultry products are mostly incriminated sources. In Egypt, it was found that S. enteritidis and S. typhimurium are the most prevalent ones in poultry farms. It is recommended to eliminate salmonella from living bird by competing for salmonella contamination in feed in order to establish a healthy gut. The Feed acidifiers are the group of feed additives containing low-molecular-weight organic acids and/ or their salts which act as performance promoters by lowering the pH in the gut, optimizes digestion and inhibit bacterial growth. The inclusion of organic acid in pure form nonetheless effective in feed, yet, it is difficult to handle in feed mills as it is corrosive and produce more losses during pelleting process. The current study aimed at to evaluate the impact of incorporation of sodium diformate (SDF) and a commercial acidifier, CA (a mixture of butyric and propionic acids and their ammonium salts) at 0.4% dietary levels on broilers performance and the control S. enteritidis infection. Two hundreds and seventy unsexed cobb chickens were allotted in one of three treatments (90/ group) which were, the control (no acidifier, C- &C+), the 0.4% SDF (SDF- & SDF +) and the 0.4% CA (CA- & CA +) dietary levels for 35 days. Before the allocation of the groups, ten extra birds and a diet sample were bacteriologically examined to ensure negative contamination with salmonella. The birds were raised on deep-litter separated pens and had free access to feed and water all the time. The experimentally formulated diets were kept at 40C. After 24h access to the different dietary treatments, all the birds in the positive groups (n=15/ replicate) were inoculated intra-crop with 0.2 ml of 24 h broth culture of S. entertidis containing 1X 107 organisms while the negative-treated groups were inoculated with the same amount of the negative broth and second inoculation was done at 22 d of age. Colocal swabs were collected individually from all birds 2 h pre-inoculation to assure the absence of salmonella, then 1, 3, 5, 7, 21 days post-inoculation to recover salmonella. Performance parameter (body weight gain and feed efficiency) were calculated. Mortalities were recorded and reisolation of the salmonella was adopted to ensure it was the inoculated ones. The results revealed that the dietary acidification with sodium diformate significantly improved broilers performance and tends to produce heavier birds as compared to the negative control and CA groups. Moreover, the dietary inclusion of both acidifiers at level of 0.4% was able to eliminate mortalities completely at the relevant inoculation time. Regarding the shedding of S. enteritidius in positive groups, the SDF treatment resulted in significant (p<0.05) cessation of the shedding at 3 days post-inoculation compared to 7 days post-inoculation for the CA-group. In conclusion, sodium diformate at 0.4% dietary level in broiler diets has a valuable effect not only on broilers performance but also by eliminating S. enteritidis the main source of salmonella contamination in poultry farms which is feed.

Keywords: acidifier, broilers, Salmonalla spp, sodium diformate

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Authors: Dali Gaganidze, Ekaterine Abashidze

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Potato is one of the main agricultural crops in Georgia. Georgia produces early and late potato varieties in almost all regions. In traditional potato growing regions (Svaneti, Samckhet javaheti and Tsalka), the yield is higher than 30-35 t/ha. Among the plant pests that limit potato production and quality, the potato cyst nematodes (PCN) are harmful around the world. Yield losses caused by PCN are estimated up to 30%. Rout surveys conducted in two geographically distinct regions of Georgia producing potatoes - Samtskhe - Javakheti and Svaneti revealed potato cyst nematode Globodera rostochiensi. The aim of the study was the Phylogenetic analyses of Globodera rostochiensi revealed in Georgia by the amplification and sequencing of 28S gen in the D3 region and intergenic ITS1-15.8S-ITS2 region. Identification of all the samples from the two Globodera populations (Samtskhe - Javakheti and Svaneti), i.e., G. rostochiensis (20 isolates) were confirmed by conventional multiplex PCR with ITS 5 universal and PITSp4, PITSr3 specific primers of the cyst nematodes’ (G. pallida, G. rostochiensis). The size of PCR fragment 434 bp confirms that PCN samples from two populations, Samtskhe- Javakheti and Svaneti, belong to G. rostochiensi . The ITS1–5.8S-ITS2 regions were amplified using prime pairs: rDNA1 ( 5’ -TTGATTACGTCCCTGCCCTTT-3’ and rDNA2( 5’ TTTCACTCGCCGTTACTAAGG-3’), D3 expansion regions were amplified using primer pairs: D3A (5’ GACCCCTCTTGAAACACGGA-3’) and D3B (5’-TCGGAAGGAACCAGCTACTA-3’. PCR products of each region were cleaned up and sequenced using an ABI 3500xL Genetic Analyzer. Obtained sequencing results were analyzed by computer program BLASTN (https://blast.ncbi.nlm.nih.gov/Blast.cg). Phylogenetic analyses to resolve the relationships between the isolates were conducted in MEGA7 using both distance- and character-based methods. Based on analysis of G.rostochiensis isolate`s D3 expansion regions are grouped in three major clades (A, B and C) on the phylogenetic tree. Clade A is divided into three subclades; clade C is divided into two subclades. Isolates from the Samtckhet-javakheti population are in subclade 1 of clade A and isolates in subclade 1 of clade C. Isolates) from Svaneti populations are in subclade 2 of clade A and in clad B. In Clade C, subclade two is presented by three isolates from Svaneti and by one isolate (GL17) from Samckhet-Javakheti. . Based on analysis of G.rostochiensis isolate`s ITS1–5.8S-ITS2 regions are grouped in two main clades, the first contained 20 Georgian isolates of Globodera rostochiensis from Svaneti . The second clade contained 15 isolates of Globodera rostochiensis from Samckhet javakheti. Our investigation showed of high genetic variation of D3 and ITS1–5.8S-ITS2 region of rDNA of the isolates of G. rostochiensis from different geographic origins (Svameti, Samckhet-Javakheti) of Georgia. Acknowledgement: The research has been supported by the Shota Rustaveli National Scientific Foundation of Georgia : Project # FR17_235

Keywords: globodera rostochiensi, PCR, phylogenetic tree, sequencing

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Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

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Authors: Gordana Branković, Vesna Dragičević, Dejan Dodig, Desimir Knežević, Srbislav Denčić, Gordana Šurlan-Momirović

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Phytic acid is a major pool in the flux of phosphorus through agroecosystems and represents a sum equivalent to > 50% of all phosphorus fertilizer used annually. Nutrition rich in phytic acid can substantially decrease micronutrients apsorption as calcium, zink, iron, manganese, copper due to phytate salts excretion by human and non-ruminant animals as poultry, swine and fish, having in common very scarce phytase activity, and consequently the ability to digest and utilize phytic acid, thus phytic acid derived phosphorus in animal waste contributes to water pollution. The tested accessions consisted of 15 genotypes of bread wheat (Triticum aestivum L. ssp. vulgare) and of 15 genotypes of durum wheat (Triticum durum Desf.). The trials were sown at the three test sites in Serbia: Rimski Šančevi (RS) (45º19´51´´N; 19º50´59´´E), Zemun Polje (ZP) (44º52´N; 20º19´E) and Padinska Skela (PS) (44º57´N 20º26´E) during two vegetation seasons 2010-2011 and 2011-2012. The experimental design was randomized complete block design with four replications. The elementary plot consisted of 3 internal rows of 0.6 m2 area (3 × 0.2 m × 1 m). Grains were grinded with Laboratory Mill 120 Perten (“Perten”, Sweden) (particles size < 500 μm) and flour was used for the analysis. Phytic acid grain content was determined spectrophotometrically with the Shimadzu UV-1601 spectrophotometer (Shimadzu Corporation, Japan). Objectives of this study were to determine: i) variability and stability of the phytic acid content among selected genotypes of bread and durum wheat, ii) predominant source of variation regarding genotype (G), environment (E) and genotype × environment interaction (GEI) from the multi-environment trial, iii) influence of climatic variables on the GEI for the phytic acid content. Based on the analysis of variance it had been determined that the variation of phytic acid content was predominantly influenced by environment in durum wheat, while the GEI prevailed for the variation of the phytic acid content in bread wheat. Phytic acid content expressed on the dry mass basis was in the range 14.21-17.86 mg g-1 with the average of 16.05 mg g-1 for bread wheat and 14.63-16.78 mg g-1 with the average of 15.91 mg g-1 for durum wheat. Average-environment coordination view of the genotype by environment (GGE) biplot was used for the selection of the most desirable genotypes for breeding for low phytic acid content in the sense of good stability and lower level of phytic acid content. The most desirable genotypes of bread and durum wheat for breeding for phytic acid were Apache and 37EDUYT /07 No. 7849. Models of climatic factors in the highest percentage (> 91%) were useful in interpreting GEI for phytic acid content, and included relative humidity in June, sunshine hours in April, mean temperature in April and winter moisture reserves for genotypes of bread wheat, as well as precipitation in June and April, maximum temperature in April and mean temperature in June for genotypes of durum wheat.

Keywords: genotype × environment interaction, phytic acid, stability, variability

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Authors: El Ghazi Safae, Cherkaoui Mounia

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Within companies, emotions have been forgotten as key elements of successful management systems. Seen as factors which disturb judgment, make reckless acts or affect negatively decision-making. Since management systems were influenced by the Taylorist worker image, that made the work regular and plain, and considered employees as executing machines. However, recently, in globalized economy characterized by a variety of uncertainties, emotions are proved as useful elements, even necessary, to attend high-level management. The work of Elton Mayo and Kurt Lewin reveals the importance of emotions. Since then emotions start to attract considerable attention. These studies have shown that emotions influence, directly or indirectly, many organization processes. For example, the quality of interpersonal relationships, job satisfaction, absenteeism, stress, leadership, performance and team commitment. Emotions became fundamental and indispensable to individual yield and so on to management efficiency. The idea that a person potential is associated to Intellectual Intelligence, measured by the IQ as the main factor of social, professional and even sentimental success, was the main problematic that need to be questioned. The literature on emotional intelligence has made clear that success at work does not only depend on intellectual intelligence but also other factors. Several researches investigating emotional intelligence impact on performance showed that emotionally intelligent managers perform more, attain remarkable results, able to achieve organizational objectives, impact the mood of their subordinates and create a friendly work environment. An improvement in the emotional intelligence of managers is therefore linked to the professional development of the organization and not only to the personal development of the manager. In this context, it would be interesting to question the importance of emotional intelligence. Does it impact organizational performance? What is the importance of emotional intelligence and how it impacts organizational performance? The literature highlighted that measurement and conceptualization of emotional intelligence are difficult to define. Efforts to measure emotional intelligence have identified three models that are more prominent: the mixed model, the ability model, and the trait model. The first is considered as cognitive skill, the second relates to the mixing of emotional skills with personality-related aspects and the latter is intertwined with personality traits. But, despite strong claims about the importance of emotional intelligence in the workplace, few studies have empirically examined the impact of emotional intelligence on organizational performance, because even though the concept of performance is at the heart of all evaluation processes of companies and organizations, we observe that performance remains a multidimensional concept and many authors insist about the vagueness that surrounds the concept. Given the above, this article provides an overview of the researches related to emotional intelligence, particularly focusing on studies that investigated the impact of emotional intelligence on organizational performance to contribute to the emotional intelligence literature and highlight its importance and show how it impacts companies’ performance.

Keywords: emotions, performance, intelligence, firms

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Authors: Rebin Mzhda Mohammed, Hoshmand Ali Hama Agha

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Excess skin, often consequential to substantial weight loss or the aging process, introduces physical discomfort, obstructs daily activities, and undermines an individual's self-esteem. As these challenges become increasingly prevalent, the need to explore viable solutions grows in significance. Extra skin removal surgery, colloquially known as body contouring surgery, has emerged as a compelling intervention to ameliorate the physical and psychological burdens of excess skin. This study undertakes a comprehensive review to illuminate the intricacies of extra skin removal surgery, encompassing its diverse procedures, associated risks, benefits, and psychological implications on patients. The methodological approach adopted involves a systematic and exhaustive review of pertinent scholarly literature sourced from reputable databases, including PubMed, Google Scholar, and specialized cosmetic surgery journals. Articles are meticulously curated based on their relevance, credibility, and recency. Subsequently, data from these sources are synthesized and categorized, facilitating a comprehensive understanding of the subject matter. Qualitative analysis serves to unravel the nuanced psychological effects, while quantitative data, where available, are harnessed to underpin the study's conclusions. In terms of major findings, the research underscores the manifold advantages of extra skin removal surgery. Patients experience a notable improvement in physical comfort, amplified mobility, enhanced self-confidence, and a newfound ability to don clothing comfortably. Nonetheless, the benefits are juxtaposed with potential risks, encompassing infection, scarring, hematoma, delayed healing, and the challenge of achieving symmetry. A salient discovery is the profound psychological impact of the surgery, as patients consistently report elevated body image satisfaction, heightened self-esteem, and a substantial enhancement in overall quality of life. In summation, this research accentuates the pivotal role of extra skin removal surgery in ameliorating the intricate interplay of physical and psychological difficulties posed by excess skin. By elucidating the diverse procedures, associated risks, and psychological outcomes, the study contributes to a comprehensive and informed comprehension of the surgery's multifaceted effects. Therefore, individuals contemplating this transformative surgical option are equipped with comprehensive insights, ultimately fostering informed decision-making, guided by the expertise of medical professionals.

Keywords: extra skin removal surgery, body contouring, abdominoplasty, brachioplasty, thigh lift, body lift, benefits, risks, psychological effects

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Authors: Jianan Sun, Ziwen Ye

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Multidimensional computerized adaptive testing (MCAT) is a popular research topic in psychometrics. It is important for practitioners to clearly know the item-trait patterns of administered items when a test like MCAT is operated. Item-trait pattern recognition refers to detecting which latent traits in a psychological test are measured by each of the specified items. If the item-trait patterns of the replenished items in MCAT item pool are well detected, the interpretability of the items can be improved, which can further promote the abilities of the examinees who attending the MCAT to be accurately estimated. This research explores to solve the item-trait pattern recognition problem of the replenished items in MCAT item pool from the perspective of statistical variable selection. The popular multidimensional item response theory model, multidimensional two-parameter logistic model, is assumed to fit the response data of MCAT. The proposed method uses the least absolute shrinkage and selection operator (LASSO) to detect item-trait patterns of replenished items based on the essential information of item responses and ability estimates of examinees collected from a designed MCAT procedure. Several advantages of the proposed method are outlined. First, the proposed method does not strictly depend on the relative order between the replenished items and the selected operational items, so it allows the replenished items to be mixed into the operational items in reasonable order such as considering content constraints or other test requirements. Second, the LASSO used in this research improves the interpretability of the multidimensional replenished items in MCAT. Third, the proposed method can exert the advantage of shrinkage method idea for variable selection, so it can help to check item quality and key dimension features of replenished items and saves more costs of time and labors in response data collection than traditional factor analysis method. Moreover, the proposed method makes sure the dimensions of replenished items are recognized to be consistent with the dimensions of operational items in MCAT item pool. Simulation studies are conducted to investigate the performance of the proposed method under different conditions for varying dimensionality of item pool, latent trait correlation, item discrimination, test lengths and item selection criteria in MCAT. Results show that the proposed method can accurately detect the item-trait patterns of the replenished items in the two-dimensional and the three-dimensional item pool. Selecting enough operational items from the item pool consisting of high discriminating items by Bayesian A-optimality in MCAT can improve the recognition accuracy of item-trait patterns of replenished items for the proposed method. The pattern recognition accuracy for the conditions with correlated traits is better than those with independent traits especially for the item pool consisting of comparatively low discriminating items. To sum up, the proposed data-driven method based on the LASSO can accurately and efficiently detect the item-trait patterns of replenished items in MCAT.

Keywords: item-trait pattern recognition, least absolute shrinkage and selection operator, multidimensional computerized adaptive testing, variable selection

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Authors: Alexia Wu, Joel Ribis, Jean-Christophe Brachet, Emmanuel Clouet, Benoit Arnal, Elodie Rouesne, Stéphane Urvoy, Justine Roubaud, Yves Serruys, Frederic Lepretre

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To enhance the safety of Light Water Reactor, accident tolerant fuel (ATF) claddings materials are under development. In the framework of CEA-AREVA-EDF collaborative program on ATF cladding materials, CEA has engaged specific studies on chromium coated zirconium alloys. Especially for Loss-of-Coolant-Accident situations, chromium coated claddings have shown some additional 'coping' time before achieving full embrittlement of the oxidized cladding, when compared to uncoated references – both tested in steam environment up to 1300°C. Nevertheless, the behavior of chromium coatings and the stability of the Zr-Cr interface under neutron irradiation remain unknown. Two main points are addressed: 1. Bulk Cr behavior under irradiation: Due to its BCC crystallographic structure, Cr is prone to Ductile-to-Brittle-Transition at quite high temperature. Irradiation could be responsible for a significant additional DBTT shift towards higher temperatures. 2. Zircaloy/Cr interface behavior under irradiation: Preliminary TEM examinations of un-irradiated samples revealed a singular Zircaloy-4/Cr interface with nanometric intermetallic phase layers. Such particular interfaces highlight questions of how they would behave under irradiation - intermetallic zirconium phases are known to be more or less stable under irradiations. Another concern is a potential enhancement of chromium diffusion into the zirconium-alpha based substrate. The purpose of this study is then to determine the behavior of such coatings after ion irradiations, as a surrogate to neutron irradiation. Ion irradiations were performed at the Jannus-Saclay facility (France). 20 MeV Kr8+ ions at 400°C with a flux of 2.8x1011 ions.cm-2.s-1 were used to irradiate chromium coatings of 1-2 µm thick on Zircaloy-4 sheets substrate. At the interface, the calculated damage is close to 10 dpa (SRIM, Quick Calculation Damage mode). Thin foil samples were prepared with FIB for both as-received and irradiated coated samples. Transmission Electron Microscopy (TEM) and in-situ tensile tests in a Scanning Electron Microscope are being used to characterize the un-irradiated and irradiated materials. High Resolution TEM highlights a great complexity of the interface before irradiation since it is formed of an alternation of intermetallic phases – C14 and C15. The interfaces formed by these intermetallic phases with chromium and zirconium show semi-coherency. Chemical analysis performed before irradiation shows some iron enrichment at the interface. The chromium coating bulk microstructures and properties are also studied before and after irradiation. On-going in-situ tensile tests focus on the capacity of chromium coatings to sustain some plastic deformation when tested up to 350°C. The stability of the Cr/Zr interface is shown after ion irradiation up to 10 dpa. This observation constitutes the first result after irradiation on these new coated claddings materials.

Keywords: accident tolerant fuel, HRTEM, interface, ion-irradiation

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Authors: Todd Enslen

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In order to attract more international students to study for undergraduate degrees in Japan, many universities have been developing English-Medium Instruction degree programs. This means that many faculty members must now teach their courses in English, which raises a number of concerns. A common misconception of English-Medium Instruction (EMI) is that teaching in English is simply a matter of translating materials. Since much of the teaching in Japan still relies on a more traditional, teachercentered, approach, continuing with this style in an EMI environment that targets international students can cause a clash between what is happening and what students expect in the classroom, not to mention what the Scholarship of Teaching and Learning (SoTL) has shown is effective teaching. A variety of considerations need to be taken into account in EMI classrooms such as varying English abilities of the students, modifying input material, and assuring comprehension through interactional checks. This paper analyzes the effectiveness of the English-Medium Instruction (EMI) undergraduate degree programs in engineering, agriculture, and science at a large research university in Japan by presenting the results from student surveys regarding the areas where perceived improvements need to be made. The students were the most dissatisfied with communication with their teachers in English, communication with Japanese students in English, adherence to only English being used in the classes, and the quality of the education they received. In addition, the results of a needs analysis survey of Japanese teachers having to teach in English showed that they believed they were most in need of English vocabulary and expressions to use in the classroom and teaching methods for teaching in English. The result from the student survey and the faculty survey show similar concerns between the two groups. By helping the teachers to understand student-centered teaching and the benefits for learning that it provides, teachers may begin to incorporate more student-centered approaches that in turn help to alleviate the dissatisfaction students are currently experiencing. Through analyzing the current environment in Japanese higher education against established best practices in teaching and EMI, three areas that need to be addressed in professional development workshops were identified. These were “culture” as it relates to the English language, “classroom management techniques” and ways to incorporate them into classes, and “language” issues. Materials used to help faculty better understand best practices as they relate to these specific areas will be provided to help practitioners begin the process of helping EMI faculty build awareness of better teaching practices. Finally, the results from faculty development workshops participants’ surveys will show the impact that these workshops can have. Almost all of the participants indicated that they learned something new and would like to incorporate the ideas from the workshop into their teaching. In addition, the vast majority of the participants felt the workshop provided them with new information, and they would like more workshops like these.

Keywords: English-medium instruction, materials development, professional development, teaching effectiveness

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Authors: Delphine Mukaneza, Lin Qiao, Wang Pengxin, Li Yan, Chen Yingyi

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Human activities on land use make the land-cover gradually change or transit. In this study, we examined the use of Landsat TM data to detect the land use change of Kigali between 1987 and 2009 using remote sensing techniques and analysis of data using ENVI and ArcGIS, a GIS software. Six different categories of land use were distinguished: bare soil, built up land, wetland, water, vegetation, and others. With remote sensing techniques, we analyzed land use data in 1987, 1999 and 2009, changed areas were found and a dynamic situation of land use in Kigali city was found during the 22 years studied. According to relevant Landsat data, the research focused on land use change in accordance with the role of remote sensing in the process of urbanization. The result of the work has shown the rapid increase of built up land between 1987 and 1999 and a big decrease of vegetation caused by the rebuild of the city after the 1994 genocide, while in the period of 1999 to 2009 there was a reduction in built up land and vegetation, after the authority of Kigali city established, a Master Plan where all constructions which were not in the range of the master Plan were destroyed. Rwanda's capital, Kigali City, through the expansion of the urban area, it is increasing the internal employment rate and attracts business investors and the service sector to improve their economy, which will increase the population growth and provide a better life. The overall planning of the city of Kigali considers the environment, land use, infrastructure, cultural and socio-economic factors, the economic development and population forecast, urban development, and constraints specification. To achieve the above purpose, the Government has set for the overall planning of city Kigali, different stages of the detailed description of the design, strategy and action plan that would guide Kigali planners and members of the public in the future to have more detailed regional plans and practical measures. Thus, land use change is significantly the performance of Kigali active human area, which plays an important role for the country to take certain decisions. Another area to take into account is the natural situation of Kigali city. Agriculture in the region does not occupy a dominant position, and with the population growth and socio-economic development, the construction area will gradually rise and speed up the process of urbanization. Thus, as a developing country, Rwanda's population continues to grow and there is low rate of utilization of land, where urbanization remains low. As mentioned earlier, the 1994 genocide massacres, population growth and urbanization processes, have been the factors driving the dramatic changes in land use. The focus on further research would be on analysis of Rwanda’s natural resources, social and economic factors that could be, the driving force of land use change.

Keywords: land use change, urbanization, Kigali City, Landsat

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Authors: Rachel Danielson, Brendan Bohannan, S.M. Tsai, Kyle Meyer, Jorge L.M. Rodrigues

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The Amazon Rainforest is a global diversity hotspot and crucial carbon sink, but approximately 20% of its total extent has been deforested- primarily for the establishment of cattle pasture. Understanding the impact of this large-scale disturbance on soil microbial community composition and activity is crucial in understanding potentially consequential shifts in nutrient or greenhouse gas cycling, as well as adding to the body of knowledge concerning how these complex communities respond to human disturbance. In this study, surface soils (0-10cm) were collected from three forests and three 45-year-old pastures in Rondonia, Brazil (the Amazon state with the greatest rate of forest destruction) in order to determine the impact of forest conversion on microbial communities involved in nitrogen fixation. Soil chemical and physical parameters were paired with measurements of microbial activity and genetic profiles to determine how community composition and process rates relate to environmental conditions. Measuring both the natural abundance of 15N in total soil N, as well as incorporation of enriched 15N2 under incubation has revealed that conversion of primary forest to cattle pasture results in a significant increase in the rate of nitrogen fixation by free-living diazotrophs. Quantification of nifH gene copy numbers (an essential subunit encoding the nitrogenase enzyme) correspondingly reveals a significant increase of genes in pasture compared to forest soils. Additionally, genetic sequencing of both nifH genes and transcripts shows a significant increase in the diversity of the present and metabolically active diazotrophs within the soil community. Levels of both organic and inorganic nitrogen tend to be lower in pastures compared to forests, with ammonium rather than nitrate as the dominant inorganic form. However, no significant or consistent differences in total, extractable, permanganate-oxidizable, or loss-on-ignition carbon are present between the two land-use types. Forest conversion is associated with a 0.5- 1.0 unit pH increase, but concentrations of many biologically relevant nutrients such as phosphorus do not increase consistently. Increases in free-living diazotrophic community abundance and activity appear to be related to shifts in carbon to nitrogen pool ratios. Furthermore, there may be an important impact of transient, low molecular weight plant-root-derived organic carbon on free-living diazotroph communities not captured in this study. Preliminary analysis of nitrogenase gene variant composition using NovoSeq metagenomic sequencing indicates that conversion of forest to pasture may significantly enrich vanadium-based nitrogenases. This indication is complemented by a significant decrease in available soil molybdenum. Very little is known about the ecology of diazotrophs utilizing vanadium-based nitrogenases, so further analysis may reveal important environmental conditions favoring their abundance and diversity in soil systems. Taken together, the results of this study indicate a significant change in nitrogen cycling and diazotroph community composition with the conversion of the Amazon Rainforest. This may have important implications for the sustainability of cattle pastures once established since nitrogen is a crucial nutrient for forage grass productivity.

Keywords: free-living diazotrophs, land use change, metagenomic sequencing, nitrogen fixation

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Authors: A. Kavita Murugkar, B. Anurag Kashyap

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With the Rights for Persons with Disabilities Act (RPWD Act) 2016, the Indian government has made it mandatory for all establishments, including Heritage Sites, to be accessible for People with Disabilities. However, recent access audit surveys done under the Accessible India Campaign by Ministry of Culture indicate that there are very few accessibility measures provided in the Heritage sites for people with disabilities. Though there are some measures for the mobility impaired, surveys brought out that there are almost no provisions for people with vision impairment (PwVI) in heritage sites thus depriving them of a reasonable physical & intellectual access that facilitates an enjoyable experience and enriching interpretation of the Heritage Site. There is a growing need to develop multisensory interpretative tools that can help the PwVI in perceiving heritage sites in the absence of vision. The purpose of this research was to examine the usability of an audio-tactile model as a haptic and sound-based strategy for augmenting the perception and experience of PwVI in a heritage site. The first phase of the project was a multi-stage phenomenological experimental study with visually impaired users to investigate the design parameters for developing an audio-tactile model for PwVI. The findings from this phase included user preferences related to the physical design of the model such as the size, scale, materials, details, etc., and the information that it will carry such as braille, audio output, tactile text, etc. This was followed by the second phase in which a working prototype of an audio-tactile model is designed and developed for a heritage site based on the findings from the first phase of the study. A nationally listed heritage site from the author’s city was selected for making the model. The model was lastly tested by visually impaired users for final refinements and validation. The prototype developed empowers People with Vision Impairment to navigate independently in heritage sites. Such a model if installed in every heritage site, can serve as a technological guide for the Person with Vision Impairment, giving information of the architecture, details, planning & scale of the buildings, the entrances, location of important features, lifts, staircases, and available, accessible facilities. The model was constructed using 3D modeling and digital printing technology. Though designed for the Indian context, this assistive technology for the blind can be explored for wider applications across the globe. Such an accessible solution can change the otherwise “incomplete’’ perception of the disabled visitor, in this case, a visually impaired visitor and augment the quality of their experience in heritage sites.

Keywords: accessibility, architectural perception, audio tactile model , inclusive heritage, multi-sensory perception, visual impairment, visitor experience

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Authors: Skyler Kim

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An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: Olasunkanmi Olapeju

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A large chunk of global population are not yet connected to water borne faecal management systems that rely on flush mechanisms and sewers networks that are linked with a central treatment plant. Only about 10% of sub-Saharan African countries are connected to central sewage systems. In Nigeria, majority of the population do not only depend on on-plot sanitation systems, a huge chunk do not also have access to safe and improved toilets. Apart from the organizational challenges and technical capacity, the other major factors that account for why faecal waste management is yet unimproved in developing countries are faulty planning frameworks that fail to maintain balance between urbanization dynamics and infrastructures, and misconceptions about what modern sanitation is all about. In most cases, the quest to implement developmental patterns that integrate modern sewers based sanitation systems have huge financial and political costs. Faecal waste management in poor countries largely lacks the needed political attention and budgetary prioritization. Yet, the on-plot sanitation systems being mainly relied upon the need to be managed in a manner that is sustainable and healthy, pending when development would embrace a more sustainable off-site central sewage system. This study is aimed at investigating existing strategies for managing on-plot sanitation systems’ faecal waste in Ogun state, Nigeria, with the aim of recommending sustainable sanitation management systems. The study adopted the convergent parallel variant of the mixed-mode technique, which involves the adoption of both quantitative and qualitative method of data collection. Adopting a four-level multi-stage approach, which is inclusive of all political divisions in the study area, a total of 330 questionnaires were respectively administered in the study area. Moreover, the qualitative data adopted the purposive approach in scoping down to 33 key informants. SPSS software (Version 22.0) was employed for descriptively analysis. The study shows that about 52% of households adopt the non-recovery management (NRM) means of burying their latrines with sand sludge shrinkage with chemicals such as carbides. The dominance of the non-recovery management means seriously constrains the quest for faecal resource recovery. Essentially, the management techniques adopted by households depend largely on the technology of their sanitary containments, emptying means available, the ability of households to pay for the cost of emptying, and the social acceptability of the reusability of faecal waste, which determines faecal resource recoverability. The study suggests that there is a need for municipal authorities in the study area to urgently intervene in the sanitation sector and consider it a key element of the planning process. There is a need for a comprehensive plan that would ensure a seamless transition to the adoption of a modern sanitation management system.

Keywords: faecal, management, planning, waste, sanitation, sustainability

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Authors: Nathaniel Oladimeji Dixon, Adekemi Dorcas Fadun

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Educational managers have observed a downward trend in the administrative effectiveness of non-teaching staff in federal universities in South-west Nigeria. This is evident in the low-quality service delivery of administrators and unaccomplished institutional goals and missions of higher education. Scholars have thus indicated the need for the deployment and adoption of a practice that encourages information collection and sharing among stakeholders with a view to improving service delivery and outcomes. This study examined the extent to which knowledge management correlated with the administrative effectiveness of non-teaching staff in federal universities in South-west Nigeria. The study adopted the survey design. Three federal universities (the University of Ibadan, Federal University of Agriculture, Abeokuta, and Obafemi Awolowo University) were purposively selected because administrative ineffectiveness was more pronounced among non-teaching staff in government-owned universities, and these federal universities were long established. The proportional and stratified random sampling was adopted to select 1156 non-teaching staff across the three universities along the three existing layers of the non-teaching staff: secretarial (senior=311; junior=224), non-secretarial (senior=147; junior=241) and technicians (senior=130; junior=103). Knowledge Management Practices Questionnaire with four sub-scales: knowledge creation (α=0.72), knowledge utilization (α=0.76), knowledge sharing (α=0.79) and knowledge transfer (α=0.83); and Administrative Effectiveness Questionnaire with four sub-scales: communication (α=0.84), decision implementation (α=0.75), service delivery (α=0.81) and interpersonal relationship (α=0.78) were used for data collection. Data were analyzed using descriptive statistics, Pearson product-moment correlation and multiple regression at 0.05 level of significance, while qualitative data were content analyzed. About 59.8% of the non-teaching staff exhibited a low level of knowledge management. The indices of administrative effectiveness of non-teaching staff were rated as follows: service delivery (82.0%), communication (78.0%), decision implementation (71.0%) and interpersonal relationship (68.0%). Knowledge management had significant relationships with the indices of administrative effectiveness: service delivery (r=0.82), communication (r=0.81), decision implementation (r=0.80) and interpersonal relationship (r=0.47). Knowledge management had a significant joint prediction on administrative effectiveness (F (4;1151)= 0.79, R=0.86), accounting for 73.0% of its variance. Knowledge sharing (β=0.38), knowledge transfer (β=0.26), knowledge utilization (β=0.22), and knowledge creation (β=0.06) had relatively significant contributions to administrative effectiveness. Lack of team spirit and withdrawal syndrome is the major perceived constraints to knowledge management practices among the non-teaching staff. Knowledge management positively influenced the administrative effectiveness of the non-teaching staff in federal universities in South-west Nigeria. There is a need to ensure that the non-teaching staff imbibe team spirit and embrace teamwork with a view to eliminating their withdrawal syndromes. Besides, knowledge management practices should be deployed into the administrative procedures of the university system.

Keywords: knowledge management, administrative effectiveness of non-teaching staff, federal universities in the south-west of nigeria., knowledge creation, knowledge utilization, effective communication, decision implementation

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Authors: Rozelle Labuschagne, Ronel Roos

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Individuals often experience a reduction in physical function, quality of life and basic activities of daily living after surgery. This is exponentially true for high-risk patients, especially the elderly and frail individuals. Not much is known about the physical function, physical activity preferences and factors associated with the six-minute walk test of elderly individuals who would undergo elective abdominal surgery in South Africa. Such information is important to design effective prehabilitation physiotherapy programs prior to elective surgery. The purpose of the study was to describe the demographic profile and physical function of elderly patients who would undergo elective surgery and to determine factors associated with their six-minute walk test distance findings. A cross-sectional descriptive study in elderly patients older than 60 years of age who would undergo elective abdominal surgery were consecutively sampled at a private hospital in Pretoria, South Africa. Participants’ demographics were collected and physical function assessed with the Functional Comorbidity Index (FCI), DeMorton Mobility Index (DEMMI), Lawton-Brody Instrumental Activities of Daily Living Scale (IADL) and six-minute walk test (6MWT). Descriptive and inferential statistics were used for data analysis with IBM SPSS 25. A p-value ≤ 0.05 were deemed statistically significant. The pilot study consisted of 12 participants (female (n=11, 91.7%), male (n=1, 8.3%) with a mean age of 65.8 (±4.5) years, body mass index of 28 (±4.2) kg.m2 with one (8.3%) participant being a current smoker and four (33.3%) participants having a smoking history. Nine (75%) participants lived independently at home and three (25%) had caregivers. Participants reported walking (n=6, 50%), stretching exercises (n=1, 8.3%), household chores & gardening (n=2, 16.7%), biking/swimming/running (n=1, 8.3%) as physical activity preferences. Physical function findings of the sample were: mean FCI score 3 (±1.1), DEMMI score 81.1 (±14.9), IADL 95 (±17.3), 6MWT 435.50 (IQR 364.75-458.50) with percentage 6MWT distance achieved 81.8% (IQR 64.4%-87.5%). A strong negative correlation was observed between 6MWT distance walked and FCI (r = -0.729, p=0.007). The majority of study participants reported incorporating some form of physical activity into their daily life as form of exercise. Most participants did not achieve their predicted 6MWT distance indicating less than optimal levels of physical function capacity. The number of comorbidities as determined by the FCI was associated with the distance that participants could walk with the 6MWT. The results of this pilot study could be used to indicate which elderly individuals would benefit most from a pre-surgical rehabilitation program. The main goal of such a program would be to improve physical function capacity as measured by the 6MWT. Surgeons could refer patients based on age and number of comorbidities, as determined by the FCI, to potentially improve surgical outcomes.

Keywords: abdominal surgery, elderly, physical function, six-minute walk test

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Authors: Inbal Zuriely, Yonit Weiss, Hilla Zaharoni, Hadas Lewkowicz, Tatiana Vander, Tarif Bader

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early active movement, along with adjusting optimal nutrition, prevents aggravation of muscle degeneracy and functional decline. Eating is a basic activity of daily life, which reflects the patient's independence. When eating and feeding are experienced successfully, they lead to a sense of pleasure and satisfaction. However, when they are experienced as a difficulty, they might evoke feelings of helplessness and frustration. This stresses the essential process of gradual weaning off the enteral feeding tube. the work describes the collaboration of a dietitian, determining the nutritional needs of patients undergoing enteral tube weaning as part of the rehabilitation process, with the suited treatment of an occupational therapist. Occupational therapy intervention regarding eating capabilities focuses on improving the required motor and cognitive components, along with environmental adjustments and aids, imparting eating strategies and training to patients and their families. The project was conducted in the long-term, ventilated patients’ department at the Herzfeld Rehabilitation Geriatric Medical Center on patients undergoing enteral tube weaning with the staff’s assistance. Establishing continuous collaboration between the dietician and the occupational therapist, starting from the beginning of the feeding-tube weaning process: 1.The dietician updates the occupational therapist about the start of the process and the approved diet. 2.The occupational therapist performs cognitive, motor, and functional assessments and treatments regarding the patient’s eating capabilities and recommends the required adjustments for independent eating according to the FIM (Functional Independence Measure) scale. 3.The occupational therapist closely follows up on the patient’s degree of independence in eating and provides a repeated update to the dietician. 4.The dietician accordingly guides the ward staff on whether and how to feed the patient or allow independent eating. The project aimed to promote patients toward independent feeding, which leads to a sense of empowerment, enjoyment of the eating experience, and progress of functional ability, along with performing active movements that will motivate mobilization. From the beginning of 2022, 26 patients participated in the project. 79% of all patients who started the weaning process from tube feeding achieved different levels of independence in feeding (independence levels ranged from supervision (FIM-5) to complete independence (FIM-7). The integration of occupational therapy and dietary treatment is based on a patient-centered approach while considering the patient’s personal needs, preferences, and goals. This interdisciplinary partnership is essential for meeting the complex needs of prolonged mechanically ventilated patients and promotes independent functioning and quality of life.

Keywords: dietary, mechanical ventilation, occupational therapy, tube feeding weaning

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Authors: Sanari Chalin Moriri, Kwabena Kingsley Ayisi, Alina Mofokeng

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Dryland smallholder farmers in South Africa are vulnerable to all kinds of risks, and it negatively affects crop productivity and profit. Pigeonpea is a leguminous and multipurpose crop that provides food, fodder, and wood for smallholder farmers. The majority of these farmers are still growing pigeonpea from traditional unimproved seeds, which comprise a mixture of genotypes. The objectives of the study were to identify the key risk factors that affect pigeonpea productivity and to develop management strategies on how to alleviate the risk factors in pigeonpea production. The study was conducted in two provinces (Limpopo and Mpumalanga) of South Africa in six municipalities during the 2020/2021 growing seasons. The non-probability sampling method using purposive and snowball sampling techniques were used to collect data from the farmers through a structured questionnaire. A total of 114 pigeonpea producers were interviewed individually using a questionnaire. Key stakeholders in each municipality were also identified, invited, and interviewed to verify the information given by farmers. Data collected were subjected to SPSS statistical software 25 version. The findings of the study were that majority of farmers affected by risk factors were women, subsistence, and old farmers resulted in low food production. Drought, unavailability of improved pigeonpea seeds for planting, access to information, and processing equipment were found to be the main risk factors contributing to low crop productivity in farmer’s fields. Above 80% of farmers lack knowledge on the improvement of the crop and also on the processing techniques to secure high prices during the crop off-season. Market availability, pricing, and incidence of pests and diseases were found to be minor risk factors which were triggered by the major risk factors. The minor risk factors can be corrected only if the major risk factors are first given the necessary attention. About 10% of the farmers found to use the crop as a mulch to reduce soil temperatures and to improve soil fertility. The study revealed that most of the farmers were unaware of its utilisation as fodder, much, medicinal, nitrogen fixation, and many more. The risk of frequent drought in dry areas of South Africa where farmers solely depend on rainfall poses a serious threat to crop productivity. The majority of these risk factors are caused by climate change due to unrealistic, low rainfall with extreme temperatures poses a threat to food security, water, and the environment. The use of drought-tolerant, multipurpose legume crops such as pigeonpea, access to new information, provision of processing equipment, and support from all stakeholders will help in addressing food security for smallholder farmers. Policies should be revisited to address the prevailing risk factors faced by farmers and involve them in addressing the risk factors. Awareness should be prioritized in promoting the crop to improve its production and commercialization in the dryland farming system of South Africa.

Keywords: management strategies, pigeonpea, risk factors, smallholder farmers

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Authors: Iris Vural Gursel, Andrea Ramirez

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Effective utilization of lignin is an important mean for developing economically profitable biorefineries. Current literature suggests that large amounts of lignin will become available in second generation biorefineries. New conversion technologies will, therefore, be needed to carry lignin transformation well beyond combustion to produce energy, but towards high-value products such as chemicals and transportation fuels. In recent years, significant progress on catalysis has been made to improve transformation of lignin, and new catalytic processes are emerging. In this work, a techno-economic assessment of two of these novel conversion routes and comparison with more established lignin pyrolysis route were made. The aim is to provide insights into the potential performance and potential hotspots in order to guide the experimental research and ease the commercialization by early identifying cost drivers, strengths, and challenges. The lignin conversion routes selected for detailed assessment were: (non-catalytic) lignin pyrolysis as the benchmark, direct hydrodeoxygenation (HDO) of lignin and hydrothermal lignin depolymerisation. Products generated were mixed oxygenated aromatic monomers (MOAMON), light organics, heavy organics, and char. For the technical assessment, a basis design followed by process modelling in Aspen was done using experimental yields. A design capacity of 200 kt/year lignin feed was chosen that is equivalent to a 1 Mt/y scale lignocellulosic biorefinery. The downstream equipment was modelled to achieve the separation of the product streams defined. For determining external utility requirement, heat integration was considered and when possible gasses were combusted to cover heating demand. The models made were used in generating necessary data on material and energy flows. Next, an economic assessment was carried out by estimating operating and capital costs. Return on investment (ROI) and payback period (PBP) were used as indicators. The results of the process modelling indicate that series of separation steps are required. The downstream processing was found especially demanding in the hydrothermal upgrading process due to the presence of significant amount of unconverted lignin (34%) and water. Also, external utility requirements were found to be high. Due to the complex separations, hydrothermal upgrading process showed the highest capital cost (50 M€ more than benchmark). Whereas operating costs were found the highest for the direct HDO process (20 M€/year more than benchmark) due to the use of hydrogen. Because of high yields to valuable heavy organics (32%) and MOAMON (24%), direct HDO process showed the highest ROI (12%) and the shortest PBP (5 years). This process is found feasible with a positive net present value. However, it is very sensitive to the prices used in the calculation. The assessments at this stage are associated with large uncertainties. Nevertheless, they are useful for comparing alternatives and identifying whether a certain process should be given further consideration. Among the three processes investigated here, the direct HDO process was seen to be the most promising.

Keywords: biorefinery, economic assessment, lignin conversion, process design

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Authors: Ella Abaev, Shany Segal, Miri Gabay

Abstract:

Background: Choking is a blockage of airways that prevents efficient breathing and air flow to the lungs. Choking may be partial or full and is an emergency situation. Complete or prolonged choking leads to apnea, lack of oxygen in the tissues of the body and brain, and can cause death. There are three mechanisms of choking: obstruction of internal respiratory tracts by food or object aspiration, any material that blocks or covers external air passages, external pressure on the neck or trapping between objects. Children's airways are narrower than that of adults and therefore the risk of choking is greater, due to the aspiration of food and other foreign bodies into the lungs. In the Child Development Center at Safra Children’s Hospital, Tel Hashomer in Israel are treated infants, toddlers, and children aged 0-18 years with various developmental disabilities. Due to the increase in reports of ‘almost an event’ of choking in the past year and the serious consequences of choking event, it was decided to give an emphasis to the issue. Incidence and methods: The number of reports of ‘almost an event’ or a choking event was examined at the center during the years 2013-2018 and a thorough research work was conducted on the subject in order to build a prevention program. Findings: Between 2013 and 2018 the center reported about ten cases of ‘almost choking events’. In the middle of 2018 alone three cases of ‘almost an event’ were reported. Objective: Providing knowledge leads to awareness raise, change of perception, change in behavior and prevention. The center employs more than 130 staff members from various sectors so that it is the work of multi-professional teams to promote the quality and safety of the treatment. The familiarity of the staff with risk factors, prevention guidelines, identification of choking signs, and treatment are most important and significant in determining the outcome of a choking event. Conclusions and recommendations: After in-depth research work was carried out in cooperation with the Risk Management Unit on the subject of choking, which include a description of the definitions, mechanisms, risk factors, treatment methods and extensive recommendations for prevention (e.g. using treatment and stimulation accessories with standards association stamps and adjustment of the type of food and the way it is served to match to the child's age and the ability to swallow). The expected stages of development and emphasis on the population of children with special needs were taken into account. The research findings will be published by the staff and parents of the patients, professional publications, and lectures and there is an expectation to decrease the number of choking events in the next years.

Keywords: children with special needs, choking, educational system, prevention guidelines

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Authors: Shuai Yuan, Minxia Shi, Xu Zhang, Jianzhi Yang, Kangqi Tian, Yuzheng Ma

Abstract:

The precise measurement of muscle activities is essential for understanding the function of various body movements. This work aims to develop a muscle magnetic field signal detection system based on mathematical analysis. Medical research has underscored that early detection of muscle atrophy, coupled with lifestyle adjustments such as dietary control and increased exercise, can significantly enhance muscle-related diseases. Currently, surface electromyography (sEMG) is widely employed in research as an early predictor of muscle atrophy. Nonetheless, the primary limitation of using sEMG to forecast muscle strength is its inability to directly measure the signals generated by muscles. Challenges arise from potential skin-electrode contact issues due to perspiration, leading to inaccurate signals or even signal loss. Additionally, resistance and phase are significantly impacted by adipose layers. The recent emergence of optically pumped magnetometers introduces a fresh avenue for bio-magnetic field measurement techniques. These magnetometers possess high sensitivity and obviate the need for a cryogenic environment unlike superconducting quantum interference devices (SQUIDs). They detect muscle magnetic field signals in the range of tens to thousands of femtoteslas (fT). The utilization of magnetometers for capturing muscle magnetic field signals remains unaffected by issues of perspiration and adipose layers. Since their introduction, optically pumped atomic magnetometers have found extensive application in exploring the magnetic fields of organs such as cardiac and brain magnetism. The optimal operation of these magnetometers necessitates an environment with an ultra-weak magnetic field. To achieve such an environment, researchers usually utilize a combination of active magnetic compensation technology with passive magnetic shielding technology. Passive magnetic shielding technology uses a magnetic shielding device built with high permeability materials to attenuate the external magnetic field to a few nT. Compared with more layers, the coils that can generate a reverse magnetic field to precisely compensate for the residual magnetic fields are cheaper and more flexible. To attain even lower magnetic fields, compensation coils designed by Biot-Savart law are involved to generate a counteractive magnetic field to eliminate residual magnetic fields. By solving the magnetic field expression of discrete points in the target region, the parameters that determine the current density distribution on the plane can be obtained through the conventional target field method. The current density is obtained from the partial derivative of the stream function, which can be represented by the combination of trigonometric functions. Optimization algorithms in mathematics are introduced into coil design to obtain the optimal current density distribution. A one-dimensional linear regression analysis was performed on the collected data, obtaining a coefficient of determination R2 of 0.9349 with a p-value of 0. This statistical result indicates a stable relationship between the peak-to-peak value (PPV) of the muscle magnetic field signal and the magnitude of grip strength. This system is expected to be a widely used tool for healthcare professionals to gain deeper insights into the muscle health of their patients.

Keywords: muscle magnetic signal, magnetic shielding, compensation coils, trigonometric functions.

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Authors: Dimitri Bacco, Arianna Trentini, Fabiana Scotto, Flavio Rovere, Daniele Foscoli, Cinzia Para, Paolo Veronesi, Silvia Sandrini, Claudia Zigola, Michela Comandini, Marilena Montalti, Marco Zamagni, Vanes Poluzzi

Abstract:

The Po Valley, in the north of Italy, is one of the most polluted areas in Europe. The air quality of the area is linked not only to anthropic activities but also to its geographical characteristics and stagnant weather conditions with frequent inversions, especially in the cold season. Even the coastal areas present high values of particulate matter (PM10 and PM2.5) because the area closed between the Adriatic Sea and the Apennines does not favor the dispersion of air pollutants. The aim of the present work was to identify the main sources of particulate matter in Rimini, a tourist city in northern Italy. Two sampling campaigns were carried out in 2018, one in winter (60 days) and one in summer (30 days), in 4 sites: an urban background, a city hotspot, a suburban background, and a rural background. The samples are characterized by the concentration of the ionic composition of the particulates and of the main a hydro-sugars, in particular levoglucosan, a marker of the biomass burning, because one of the most important anthropogenic sources in the area, both in the winter and surprisingly even in the summer, is the biomass burning. Furthermore, three sampling points were chosen in order to maximize the contribution of a specific biomass source: a point in a residential area (domestic cooking and domestic heating), a point in the agricultural area (weed fires), and a point in the tourist area (restaurant cooking). In these sites, the analyzes were enriched with the quantification of the carbonaceous component (organic and elemental carbon) and with measurement of the particle number concentration and aerosol size distribution (6 - 600 nm). The results showed a very significant impact of the combustion of biomass due to domestic heating in the winter period, even though many intense peaks were found attributable to episodic wood fires. In the summer season, however, an appreciable signal was measured linked to the combustion of biomass, although much less intense than in winter, attributable to domestic cooking activities. Further interesting results were the verification of the total absence of sea salt's contribution in the particulate with the lower diameter (PM2.5), and while in the PM10, the contribution becomes appreciable only in particular wind conditions (high wind from north, north-east). Finally, it is interesting to note that in a small town, like Rimini, in summer, the traffic source seems to be even more relevant than that measured in a much larger city (Bologna) due to tourism.

Keywords: aerosol, biomass burning, seacoast, urban area

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Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

Abstract:

Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

Procedia PDF Downloads 126